Triple

T2513605
Position Surface form Disambiguated ID Type / Status
Subject Three-Lakes Region E52756 entity
Predicate hasTown P847 FINISHED
Object Murten E315007 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Murten | Statement: [Three-Lakes Region, hasTown, Murten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Murten
Context triple: [Three-Lakes Region, hasTown, Murten]
  • A. Murten chosen
    Murten is a historic bilingual town in the canton of Fribourg, Switzerland, known for its well-preserved medieval old town and lakeside setting on Lake Murten.
  • B. Grenchen
    Grenchen is a Swiss town in the canton of Solothurn known for its watchmaking industry and location at the foot of the Jura Mountains.
  • C. Richterswil
    Richterswil is a picturesque municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland.
  • D. Chexbres
    Chexbres is a picturesque Swiss village in the canton of Vaud, renowned for its terraced vineyards overlooking Lake Geneva and its location within the UNESCO-listed Lavaux wine-growing region.
  • E. Liestal
    Liestal is a historic Swiss town in northwestern Switzerland that serves as the administrative and cultural center of the canton of Basel-Landschaft.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ab4958e76481908a235377dd921c9e completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd20c8ab0819096d6a654039beb39 completed March 7, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69b2357438648190b2dc11ae9b568a15 completed March 12, 2026, 3:39 a.m.
Created at: March 6, 2026, 9:46 p.m.